Solutions · Argus Pentest

Authenticated penetration testing for Oil, Gas & Energy

Authenticated penetration testing for oil, gas & energy. Energy operators manage safety-critical procedures and vast equipment and materials catalogues across field sites.

Authenticated Security Testing for Critical Energy Infrastructure

Energy operators manage safety-critical procedures and vast equipment catalogues across diverse field sites, requiring robust protection for the enterprise web applications and APIs that underpin these operations. Allmaz provides authenticated dynamic security scanning designed to secure these complex environments, ensuring that safety SOPs and supplier records remain protected from unauthorized access through rigorous, deep-surface testing. As one of the three core engines of the Argus self-hosted AI testing platform, this security engine shares a unified runtime, model layer, credential store, and cost ledger with the QA and AI engines. By leveraging a modular architecture and a self-hosted deployment model, it allows energy organizations to maintain complete control over their security posture without relying on external SaaS dependencies, ensuring that sensitive scan data and credentials never leave the internal infrastructure.

Capabilities

Strengthening Energy Sector Resilience

Deep visibility into authenticated surfaces that extend far beyond the initial login page

Complete data sovereignty and compliance via a fully self-hosted infrastructure

Elimination of accidental scanning risks through the use of explicit, deliberate allow-lists

Secure credential management utilizing a shared, encrypted platform store

Rapid remediation enabled by detailed severity-based reporting in HTML and JSON formats

Future-proof flexibility via a modular open-source engine that can be upgraded without platform disruption

Engineered for High-Stakes Environments

Authenticated Dynamic Scanning

Unlike generic scanners, our system uses a scripted login to obtain session cookies and bearer tokens, operating as a real logged-in user to test internal application logic.

Synthesized API Discovery

Endpoints discovered during the login and crawl process seed a synthesized API spec, allowing the scan to reach deep authenticated surfaces.

Self-Hosted Architecture

Scan data, credentials, and reports stay on your own infrastructure with no external SaaS dependency, meeting strict energy sector compliance.

AI-Driven Payload Generation

The integrated model is used specifically for payload generation and finding triage to identify vulnerabilities more effectively.

Modular Scanner Engine

Powered by Deep Eye, an open-source engine driven via CLI, allowing for upgrades or replacements without disrupting the platform.

The Authenticated Testing Workflow

1Define an explicit allow-list of approved targets to ensure scanning is controlled and deliberate.
2Execute a scripted login using the encrypted credential store to acquire session cookies and bearer tokens.
3Crawl the application to discover endpoints and synthesize an API specification.
4Perform dynamic security scanning across the authenticated surface of the web application and APIs.
5Generate HTML and JSON reports categorized by severity for technical and management review.

Technical and Operational FAQ

How is sensitive credential data handled during scans?

Credentials are managed through a secure, encrypted credential store shared across the Argus platform, ensuring that session cookies and bearer tokens are handled safely during the scripted login process.

Can this tool accidentally scan unauthorized field equipment or targets?

No. The system operates on a strict allow-list basis; scans run only against targets that have been deliberately added to the approved list, preventing accidental interaction with unauthorized assets.

Where is the scan data and reporting stored?

The platform is entirely self-hosted. All scan data, credentials, and resulting reports remain on your own internal infrastructure with no external SaaS dependency.

What happens if the scanner fails to authenticate into the application?

The system applies an 'honest-failure' rule: if the scanner cannot authenticate, it is recorded as an environment failure rather than a security finding, preventing false positives in the security report.

How does the AI model contribute to the scanning process?

The AI model is used exclusively for payload generation and finding triage (text-in, text-out) to improve the accuracy of vulnerability detection without utilizing vision capabilities.

Secure Your Operational Technology

Protect your safety-critical procedures and materials master data with authenticated penetration testing.

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